How is the latent vector transforming to a feature map in DCGAN (Generator structure)?
Noise vector (batch_size, 100, 1, 1) is deconvoloved with filter_1 (100, 4, 4). Result is feature_map_1 (1, 4, 4). And since there are 512 filters, so there will be 512 feature maps. Output shape will be (batch_size, 512, 4, 4).
I think you need better undersanting for convolutional calculations in general. In this stack it was explained very well.